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Trust Region Filter-SQP Method for Multi-Fidelity Wing Aerostructural Optimization

In: Variational Analysis and Aerospace Engineering

Author

Listed:
  • Ali Elham

    (Delft University of Technology)

  • Michel J. L. van Tooren

    (University of South Carolina)

Abstract

A trust region filter-SQP method is used for wing multi-fidelity aerostructural optimization. Filter method eliminates the need for a merit function, and subsequently a penalty parameter. Besides, it can easily be modified to be used for multi-fidelity optimization. A low fidelity aerostructural analysis tool is presented, that computes the drag, weight, and structural deformation of lifting surfaces as well as their sensitivities with respect to the design variables using analytical methods. That tool is used for a mono-fidelity wing aerostructural optimization using a trust region filter-SQP method. In addition to that, a multi-fidelity aerostructural optimization has been performed, using a higher fidelity CFD code to calibrate the results of the lower fidelity model. In that case, the lower fidelity tool is used to compute the objective function, constraints, and their derivatives to construct the quadratic programming subproblem. The high fidelity model is used to compute the objective function and the constraints used to generate the filter. The results of the high fidelity analysis are also used to calibrate the results of the lower fidelity tool during the optimization. This method is applied to optimize the wing of an A320 like aircraft for minimum fuel burn. The results showed about 9 % reduction in the aircraft mission fuel burn.

Suggested Citation

  • Ali Elham & Michel J. L. van Tooren, 2016. "Trust Region Filter-SQP Method for Multi-Fidelity Wing Aerostructural Optimization," Springer Optimization and Its Applications, in: Aldo Frediani & Bijan Mohammadi & Olivier Pironneau & Vittorio Cipolla (ed.), Variational Analysis and Aerospace Engineering, pages 247-267, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-45680-5_10
    DOI: 10.1007/978-3-319-45680-5_10
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